function [c_l,c_h]=mc(ability_metric,parameter,LowCost_Ability,HighCost_Ability,LowCost_Error,HighCost_Error)

%N=size(LowCost_Ability,1);

% Parameters that are estimated 
theta         =parameter(2);
sigma_epsilon =parameter(5);        


if ability_metric==1
    c_l=1* LowCost_Ability.^(-1*theta);            % (1596 out of 2157 matches = 74%) 1. Ability proxy is pre-match winning probability (betting odds)
    c_h=1*HighCost_Ability.^(-1*theta);            % (used only for observations where pre-match odds are available for both players)
elseif ability_metric==2.5
    c_l=1* LowCost_Ability.^theta;                 % (1871 out of 2670 matches = 70%) 2.5. Ability proxy is WTA rank but more granular than 1-9->1^theta, 10-19->2^theta, etc
    c_h=1*HighCost_Ability.^theta;                 % (used only for observations where WTA ranks are available for both players)
elseif ability_metric==4
    c_l=1*exp(-1*theta* LowCost_Ability);          % (1870 out of 2670 matches = 70%) 4. Ability proxy is WTA z-score (normalized ranking points)
    c_h=1*exp(-1*theta*HighCost_Ability);          % (used only for observations where WTA ranking points are available for both players)
end


c_l=c_l+sigma_epsilon*LowCost_Error;
c_h=c_h+sigma_epsilon*HighCost_Error;


end